Determination of Traffic Accident Black Spot Based on Geographical Information System: The Empirical Bayes Application

2015 ◽  
Author(s):  
Mehmet Ali DERELİ ◽  
Saffet ERDOĞAN ◽  
Ömer SOYSAL ◽  
Alper ÇABUK ◽  
Murat UYSAL ◽  
...  
Keyword(s):  
Information System ◽  
Geographical Information System ◽  
Traffic Accident ◽  
Empirical Bayes ◽  
Black Spot ◽  
Geographical Information

scholarly journals DETERMINAÇÃO DA CAPACIDADE DE USO DAS TERRAS DO MUNICÍPIO DE SÃO MANUEL - SP

Irriga ◽  
2003 ◽  
Vol 8 (2) ◽  
pp. 142-149
Author(s):  
Osmar Delmanto Júnior ◽  
Sergio Campos ◽  
Lincoln Gehring Cardoso ◽  
Zacarias Xavier de Barros
Keyword(s):  
Land Use ◽  
Information System ◽  
Geographical Information System ◽  
Geographical Information Systems ◽  
Geographical Information ◽  
Digital Storage ◽  
Territorial Organization ◽  
E Mail ◽  
Excellent Tool

DETERMINAÇÃO DA CAPACIDADE DE USO DAS TERRAS DO MUNICÍPIO DE SÃO MANUEL - SP   Osmar Delmanto JuniorSérgio CamposLincoln Gehring CardosoZacarias Xavier  de BarrosDepartamento de Engenharia Rural, Faculdade de Ciências Agronômicas, Universidade Estadual Paulista, Botucatu, SP. CP 237, CEP 18603-970. E-mail: [email protected]  1 RESUMO  Esse trabalho objetivou a elaboração da carta de capacidade de uso das terras do Município de São Manuel - SP, visando o planejamento adequado da ocupação do solo, utilizado-se de Sistema de Informação Geográfica (SIG).  A bacia situa-se entre as coordenadas geográficas  22º 28’ 20” e 22º 53’ 10” de latitudes S e os meridianos 48º 21’ 52” e 48º 48’ 00” de longitudes W Gr., apresentando uma área de 60.988ha.   O mapa de capacidade de uso da terra do município foi elaborado a partir dos mapas de classes de declive e de solo, tomando-se por base as características de cada um e utilizando-se da tabela de julgamento de classes de capacidade de uso.  As áreas da classe e subclasses de capacidade de uso das terras determinadas pelo SIG –IDRISI foram:  IIe,s (22,64%); IIIe (8,62%); IIIe,s (15,83%); IIIs (29,97%); IVe (10,82%); VIe (3,95%) e VIIe (0,96%).  Os resultados permitiram inferir que as subclasses mais significativas foram a IIIs e IIe,s.  As classes de declive de 0 a 20% ocorrem em mais de ¾ do Município, sendo as áreas planas, as mais representativas, pois ocorrem em quase 1/3 da área total.  O SIG mostrou-se uma excelente ferramenta para determinação da capacidade de uso da terra, demonstrando que a utilização do geoprocessamento facilita e agiliza o cruzamento dos dados digitais, permitindo seu armazenamento, que poderão ser utilizados para outras análises em futuros planejamentos geoambientais.  UNITERMOS: Sistema de Informações Geográficas, unidades de solo, classes  de declive, capacidade de uso da terra   DELMANTO JUNIOR, O.; CAMPOS S.; CARDOSO, L.G.; BARROS, Z.X. LAND USE CAPABILITY DETERMINATION OF SÃO MANUEL MUNICIPALITY-SP   2 ABSTRACT  The present work purposed a land use capability chart development from São Manuel Municipality-SP using a Geographical Information System - Idrisi aiming to contribute for a better territorial organization and soil occupation planning. The basin is located in the 22º 28’ 20” geographical co-ordinates at 22º 53’ 10” S latitude, 48º 21’ 52” and 48º 48’ 00” meridian of W Gr. longitude, presenting an area of 9180,12ha.  The chart of the basin land use capability was elaborated from the soil and sloping class charts based on each one characteristics and using the class table of use capability. The class and subclass areas determined through the Geographical Information System IDRISI presented the following values: IIe,s (22,64%), IIIe (8,62%), IIIe,s (15,83%), IIIs (29,97%), IVe (10,82%), VIe (3,95%) and VIIe (0,96%).  The results allowed to infer that the most significant sub classes were IIIs and IIe,s. The 0 to 20% sloping classes have occurred in more than ¾ of the district. Plane areas were the most significant since they occur in nearly 1/3 of the whole area. The Geographical Information System IDRISI has been an excellent tool to determine land use capability, specially related with geo-processing use. The later also facilitates the input, analysis and display of spatial environmental information as well as data digital storage which could be used for other analyses in further geo-environmental design.  KEYWORDS: Geoprocessing, land-use capability, Geographical Information Systems.

scholarly journals Implementation of Heat Maps in Geographical Information System – Exploratory Study on Traffic Accident Data

2018 ◽  
Vol 10 (1) ◽  
pp. 367-384 ◽  
Author(s):  
Rostislav Netek ◽  
Tomas Pour ◽  
Renata Slezakova
Keyword(s):  
Information System ◽  
Geographical Information System ◽  
Spatial Data ◽  
Exploratory Study ◽  
Traffic Accident ◽  
Geographical Information ◽  
Negative Feeling ◽  
Heat Map ◽  
Heat Maps ◽  
Accident Data

Abstract In this study, the authors created an overview of the usage of heat maps as a GIS visualization method. In the first part of the paper, a significant number of studies was evaluated, and the technique was thoroughly described to set up a base level for further research. At this moment, the most used input data for heat maps are point data. While these data fit the method very well, also studies based on line and polygon data were found. The second part of the paper is devoted to an exploratory study on traffic accident data of the Olomouc city, Czech Republic. Even spatial distribution of the dataset by geographical information system makes it the perfect example of heat map usage. These data were visualized in multiple ways changing color range, kernel size, radius, and transparency. Two groups of users were created in order to evaluate these heat maps. One group was consisting of those educated or working in cartography. The second one was consisting of the general public. Created heat maps were shown to these volunteers and their task was to decide their preferred solution. Most of the users chose bright colors with a negative feeling, such as red, for traffic accident visualization. The best settings for transparency was identified to be around 50%. The final questions were about map readability based on radius. This setting is tied to map scale but follows a common trend throughout the research. The results of this work are a general set of recommendations and specific evaluation of the exploratory study regarding traffic accidents spatial data. The general recommendations include basic principles of the method, implementation by GIS, suitable data and correct usage of heat maps. The evaluation is answering specific questions regarding heat map settings, style and presentation in the specific case.

scholarly journals Evaluation of Methods of Peak Runoff Determination using Catchment Characteristics for Jere Sub-basin, Gurara River Basin, North Central Nigeria

2018 ◽  
Vol 13 (1) ◽  
pp. 26
Author(s):  
Mudashiru R.B. ◽  
Salami A.W. ◽  
Bilewu S.O.
Keyword(s):  
Information System ◽  
Geographical Information System ◽  
Morphometric Analysis ◽  
Morphometric Parameters ◽  
Geographical Information ◽  
Return Periods ◽  
North Central ◽  
Peak Runoff ◽  
Evaluation Of Methods

This paper presents the evaluation of methods of determination of peak runoff for an ungauged catchment. The present study made use of Geographical Information System (GIS) for the morphometric analysis of four sub-catchments within Jere sub-basin in Gurara Basin, Nigeria. Various morphometric parameters were computed and analyzed as sub-basin characteristics are important factors in determining the runoff. Three methods of peak runoff estimation were used to determine peak runoff of the study area for four return periods. The results of the peak runoff estimation based on rational method for the four sub-catchments for 25-year, 50-year, 75-year and 100-year return periods varied between 224m3/s and 1036m3/s, while the results for the SCS method varied between 105.3m3/s and 162.05m3/s and the results from the Cypress Creek method varied between 22.8m3/s and 86.55m3/s. The results obtained from the three methods showed that there are significant differences in the peak runoff results and also there are significant differences in the peak runoff results for the different return periods.

scholarly journals Identification of Traffic Accident Hotspots using Geographical Information System (GIS)

2019 ◽  
Vol 9 (2) ◽  
pp. 4429-4438
Keyword(s):  
Information System ◽  
Geographical Information System ◽  
Statistical Methods ◽  
Traffic Safety ◽  
Traffic Accident ◽  
Road Traffic ◽  
Geographical Information ◽  
Future Research ◽  
Hotspot Analysis ◽  
Road Traffic Safety

Limiting the number andseverity of traffic accidents is one of the major goals of road traffic safety management.The alarming rate of road accidents globally emphasizes the importance of an effective traffic safety management system. Identification of accident hotspots is the first step towards implementation of efficient traffic safety management.Until the arrival of Geographical Information System (GIS),traffic accident analyses have been performed based ontraditional statistical methods alone. The advent of GIS-based techniques has led toimproved traffic accident analysis by employing spatial statistics,enabling engineers and researchers to account for variation in the spatial characteristics of hotspot locations in the analysis. This paper discusses the different spatial and statistical methods that are employedintraffic accident hotspots identification. An example application of Planar Kernel Density Estimation (PKDE)for hotspot identification is presented based on crash data for Des Moines city of Iowa state. The effect of varying bandwidths in creating density mapsis investigated and the optimum bandwidth to obtain distinct hotspots is identified as 500 m for the chosen study area.The paper also discusses the scope for future research in traffic accident hotspot analysis.

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